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Low-voltage electricity customer profiling based on load data clustering

https://doi.org/10.1145/1620432.1620472
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.patcog.2009.03.030openalex-snapshot
A time series representation model for accurate and fast similarity detection
inferredcites →https://doi.org/10.1049/cp:20051383openalex-snapshot
The telegestore project in ENEL's metering system
inferredcites →https://doi.org/10.1049/ip-gtd:20041243openalex-snapshot
Emergent electricity customer classification
inferredcites →https://doi.org/10.1109/isplc.2007.371050openalex-snapshot
Keynote I. Telegestore Project Progresses And Results
inferredcites →https://doi.org/10.1109/pecon.2006.346624openalex-snapshot
Load Profiling Method in Detecting non-Technical Loss Activities in a Power Utility
inferredcites →https://doi.org/10.1109/tpwrs.2005.846234openalex-snapshot
An Electric Energy Consumer Characterization Framework Based on Data Mining Techniques
inferredcites →https://doi.org/10.1109/tpwrs.2006.873122openalex-snapshot
Comparisons Among Clustering Techniques for Electricity Customer Classification
inferredcites →https://doi.org/10.1109/tpwrs.2007.901287openalex-snapshot
Two-Stage Pattern Recognition of Load Curves for Classification of Electricity Customers
inferredcites →https://doi.org/10.5772/6250openalex-snapshot
Load Time-Series Classification Based on Pattern Recognition Methods

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Demand Forecasting in Smart Grids
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Clustering complex time‐series databases by using periodic components
inferred← citeshttps://doi.org/10.1007/978-3-319-64635-0_14openalex-snapshot
Prediction Models for Short-Term Load and Production Forecasting in Smart Electrical Grids
inferred← citeshttps://doi.org/10.1007/978-981-16-9360-1_3openalex-snapshot
Load Profiling Considering Shape Similarity Using Shape-Based Clustering
inferred← citeshttps://doi.org/10.1007/s13042-013-0185-1openalex-snapshot
Computational awareness for smart grid: a review
inferred← citeshttps://doi.org/10.1016/j.apenergy.2016.10.040openalex-snapshot
A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring
inferred← citeshttps://doi.org/10.1016/j.egyr.2025.09.002openalex-snapshot
A data-driven methodology for deriving electricity consumption typologies from smart meters
inferred← citeshttps://doi.org/10.1016/j.enbuild.2018.07.011openalex-snapshot
Disaggregating high-resolution gas metering data using pattern recognition
inferred← citeshttps://doi.org/10.1016/j.jclepro.2018.12.067openalex-snapshot
A shape-based clustering method for pattern recognition of residential electricity consumption
inferred← citeshttps://doi.org/10.1016/j.rser.2017.05.124openalex-snapshot
A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings
inferred← citeshttps://doi.org/10.1109/bigdata50022.2020.9378483openalex-snapshot
Large-scale Data-driven Segmentation of Banking Customers
inferred← citeshttps://doi.org/10.1109/isccsp.2014.6877810openalex-snapshot
Power disaggregation of domestic smart meter readings using dynamic time warping
inferred← citeshttps://doi.org/10.1109/jiot.2023.3243086openalex-snapshot
A Novel Evasion Attack Against Global Electricity Theft Detectors and a Countermeasure
inferred← citeshttps://doi.org/10.1109/smc.2013.495openalex-snapshot
A Brief Introduction to Classification for Smart Grid
inferred← citeshttps://doi.org/10.1109/tsg.2020.3017777openalex-snapshot
Develop Load Shape Dictionary Through Efficient Clustering Based on Elastic Dissimilarity Measure
inferred← citeshttps://doi.org/10.21914/anziamj.v54i0.6743openalex-snapshot
Pattern recognition and segmentation of smart meter data
inferred← citeshttps://doi.org/10.3390/en15051741openalex-snapshot
Towards a Rigorous Consideration of Occupant Behaviours of Residential Households for Effective Electrical Energy Savings: An Overview
inferred← citeshttps://doi.org/10.7177/sg.2014.v9.n3.a10openalex-snapshot
Uso de Múltiplos Canais de Atendimento: Estudo sobre o Comportamento dos Consumidores da Ampla Energia S.A. Utilizando Técnicas de Mineração de Dados
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